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Record W2161438385 · doi:10.1093/jpepsy/jsr067

Graduate Admissions in Pediatric Psychology: The Importance of Undergraduate Training

2011· article· en· W2161438385 on OpenAlexafffund
Bryan T. Karazsia, C. Meghan McMurtry

Bibliographic record

VenueJournal of Pediatric Psychology · 2011
Typearticle
Languageen
FieldMedicine
TopicMedical Education and Admissions
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsPediatric psychologyMedical educationUndergraduate educationGraduate studentsPsychologyIdeal (ethics)MedicineClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: To determine the minimum and ideal undergraduate experiences in pediatric psychology expected by graduate faculty; to determine the experiences current trainees gained prior to graduate admission; to compare trainee experiences with faculty expectations. METHODS: Faculty and current trainees completed surveys. RESULTS: Faculty expectations of minimum and ideal undergraduate training were highest for research methods and evaluation, paralleling the highest level of undergraduate training reported by trainees. Research goodness of fit also emerged as a critical admissions factor. CONCLUSIONS: The results offer empirical evidence for desirable undergraduate training related to pediatric psychology, particularly with respect to research experiences. The findings have implications for prospective trainees, faculty who mentor undergraduates, and graduate faculty serving on admissions committees.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.219
GPT teacher head0.432
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2011
Admission routes2
Has abstractyes

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